Hadoop and all it's ecosystem have settled down for good (or bad) in our hearts and / or minds. It's quite old and has proven to be quite reliable for certain kinds of tasks. Yet one problem still remains - writing Map Reduce jobs in plain Java is really a pain. The API is clunky and does it's best to hide the actual algorithm beneath tons of boilerplate.

Luckily there are abstractions on top of it - like the great Cascading library, and the even better Scalding DSL built on top of it.

During this talk we'll execute what looks like a Scala map() but using a few dozen worker nodes, and then explore some of the more advanced features of Scalding - like joins, aggregation tricks and tips on how to build not only Jobs, but entire MapReduce Pipelines.

Konrad is a late-night passionate dev living by the motto "Life is Study!". His favourite discussion topics range from distributed systems and type systems to capybaras. In those rare times he's not coding, he spreads the joy of computer science, through helping local user groups and whitepaper reading clubs.

To view the video visit www.parleys.com.

To get started building reactive applications visit http://www.typesafe.com/activator.